The increasing growth in urban population and vehicular volume coupled with inefficient traffic management results in traffic congestion on road networks. In this work, a smart/intelligent traffic signal control system was developed for two inter-dependent intersections in Akure, Nigeria. The system developed in this work uses deep learning and computer vision techniques to estimate the density of traffic and uses this information to adaptively switch traffic signals based on the traffic density estimated. Simulation results show that in 30 minutes of simulation, 32 signal cycles can be achieved and 967 vehicles can move at these two inter-dependent intersections
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